Public Transport Modeling for Commuting in Cities with Different Development Levels Using Extended Theory of Planned Behavior


Arslannur B., TORTUM A.

SUSTAINABILITY, cilt.15, sa.15, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 15 Sayı: 15
  • Basım Tarihi: 2023
  • Doi Numarası: 10.3390/su151511931
  • Dergi Adı: SUSTAINABILITY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Aerospace Database, Agricultural & Environmental Science Database, CAB Abstracts, Communication Abstracts, Food Science & Technology Abstracts, Geobase, INSPEC, Metadex, Veterinary Science Database, Directory of Open Access Journals, Civil Engineering Abstracts
  • Anahtar Kelimeler: extended TPB model, PLS-SEM, multigroup analysis, public transportation, travel behavior, SELF-EFFICACY, TRAVEL-MODE, PAST BEHAVIOR, CHOICE, PLS, SATISFACTION, INTENTION, BELIEFS, IMPACT, HABIT
  • Atatürk Üniversitesi Adresli: Evet

Özet

Reducing the use of private vehicles and promoting public transportation (PT) have always been the primary policy objectives of transport authorities. This study aims to model the factors affecting intentions and behaviors of employees to use PT for their commutes by creating an extended theory of planned behavior (ETPB). The ETPB model's applicability was evaluated using the Partial Least Squares Structural Equation Model (PLS-SEM) technique on a total of 2048 employees in three distinct cities. Then, the Multigroup analysis (MGA) method was used to compare various cities, and demographic variables such as age, education, gender, household income, and walking time to nearest PT stop. The analysis revealed that attitude, perceived norm, and personal agency have a statistically positive influence on employees' intention to use PT. Moreover, behavioral capability, intention, and habit have a positive effect on PT use, whereas environmental constraints have a negative effect. The results of the MGA analysis revealed significant differences between regions, particularly in terms of environmental factors, intention, and habit. Similarly, the article describes disparities that have emerged according to other demographic variables. The findings imply that interventions by decision makers have the potential to alter the mode of transportation chosen for commuting.